Monthly Archives: October 2017

FTSE Russell recently reported that market share of passive ETFs and mutual funds has grown from 12% in January 1998 to 46% at the end of December 2016. They carefully define “passive” as funds that are intended to replicate market capitalization weighted indexes by holding the underlying assets. Specifically excluded from this definition are other than cap weighted indexes and funds that hold options instead of the underlying. Goldman Sachs agrees with this trend if not the exact number, reporting a change from 17% passive to 38% between 2005 and 2016.

This trend has not gone unnoticed by the active management world. Analysts at Bernstein warn that the rise of passive investing may be worse than Marxism. Similarly, analysts at CLSA call it “investor socialism.” There is fear that the blind investment into all companies on a cap weighted basis will overwhelm the impact of active managers, who invest based on their research and due diligence efforts. Additionally, the momentum effect of passive investors might be expected to result in the largest and most often index-listed companies growing to even larger market capitalizations with higher valuations, and being added to even more indexes, regardless of their economic value. However, available data has not borne this out.

Note: Dispersion is defined as the percentage of stocks in the Russell 3000 Index that have either outperformed or underperformed the index by at least 10 percentage points.

Data from Zacks.com shows that the equities comprising the S&P 500 individually have betas ranging from -0.02 to 2.79. Recognizing that this is a somewhat circular reference, only one stock has a negative beta, meaning that when the market moves up, on average they are ALL moving up. This data implies that it may be difficult to implement a long-short strategy, because the equities that underperform in a rising market are still rising, even those that underperform the most. Beta is defined here as a 5 year calculation based on monthly returns. This is important, because it means that the betas are based entirely on bull market data. So they are all moving up together, but not equally. Active opportunities exist.

Another measure of active opportunity within the stock market is the CBOE implied correlation index. If passive investing really overwhelms active, you would expect to see correlations rise. This effect has not been seen in the data. See detailed explanation from Henry Ma, https://www.etftrends.com/is-there-a-passive-investing-bubble/.

Another way to look at how passive holdings might impact market function or efficiency is to compare price volatility of individual stocks in comparison to the proportion of their shares that are held in passive funds. If passive funds are holding and not trading shares, liquidity may suffer causing spreads to increase. Savita Subramanian at BAML has found that as the passively held proportion increases, prices become stickier; equity price adjustments based on earnings surprises are not as quickly reflected in price. In contrast, Pravit Chintawongvanich of Macro Risk Advisors looked at realized volatility versus percent passive ownership and did not find any effect.

Arbitrage price theory posits that if an arbitrage is available, market participants will make that trade until prices reach an equilibrium where the arbitrage is no longer available. This suggests that if the market is becoming less efficient, active traders should have an advantage and active funds should show better results. It is only one data point, but the most recent SPIVA report (https://us.spindices.com/search/?ContentType=SPIVA) shows that active fund performance has been improving over the first half of this year.

Although active managers continue to suffer outflows to passive funds, there is scant evidence to this point that passive investing has distorted the market to the point that active investors cannot impact prices. Active investing is necessary and, in fact, makes passive investing possible by providing price discovery for passive equity buyers.

Self-Driving Cars Reach New Milestone – for those readers who are still reluctant to believe in the electric car and self-driving car revolutions, we understand (but it’s time to start believing). Where the U.S. government is generally snail-pace slow in legislating in lockstep with technological change, they have passed a bill that creates a national framework of regulations for the industry. The bill includes amendments covering cybersecurity issues and allows automakers to sell up to 80,000 self-driving vehicles annually, assuming that safety standards are met. On the automakers front, it’s been an active week as Ford detailed a strategy for future investment of research and resources into self-driving cars. General Motors followed suit by indicating that its ‘Cruise Automation’ business is making rapid progress on fully autonomous driving capabilities.

Lots of hate on Tesla and Elon Musk is a continuing theme, but Tesla just keeps on keepin’ on. As soon as production of the Model 3 ramps up to plan, electric cars are a done deal and cannot be stopped. I’m not sure why Zero Hedge has such an axe to grind (lots of MLP and energy positions, perhaps?), but they sure do. Here’s a couple of the latest screeds: http://www.zerohedge.com/news/2017-10-07/visualizing-many-failures-elon-musk

In this view, your mind is composed of lots of specialized modules—modules for sizing up situations and reacting to them—and it’s the interplay among these modules that shapes your behavior. And much of this interplay happens without conscious awareness on your part. The modular model of the mind, though still young and not fully fleshed out, holds a lot of promise. For starters, it makes sense in terms of evolution: the mind got built bit by bit, chunk by chunk, and as our species encountered new challenges, new chunks would have been added. As we’ll see, this model also helps make sense of some of life’s great internal conflicts, such as whether to cheat on your spouse, whether to take addictive drugs, and whether to eat another powdered-sugar doughnut.

Now modules aren’t physical structures in the brain, just like apps aren’t hardware in your phone. They’re software; the human nature algorithms that Mother Nature coded over thousands of generations of evolution.

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Whichever module has the most emotional kick attached to it at any point wins the competition to be “you.”

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Buddhism recognized this problem over 1000 years ago. And it also came up with a solution: mindfulness meditation.